Having the Second Leg At Home - Advantage in the UEFA Champions League Knockout Phase?

In soccer knockout ties which are played in a two-legged format the team having the return match at home is usually seen as advantaged. For checking this common belief, we analyzed matches of the UEFA Champions League knockout phase since 1995. It is shown that the observed differences in frequencies of winning between teams first playing away and those which are first playing at home can be completely explained by their performances on the group stage and - more importantly - by the teams' general strength

Analysis of DCE-MRI Data using a Nonnegative Elastic Net

We present a nonnegative Elastic Net approach for the analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging data. A multi-compartment approach is considered, which is translated into a (restricted) least square model selection problem. This is done by using a set of basis functions for a given set of candidate rate constants. The form of the basis functions is derived from a kinetic model and thus describes the contribution of some compartment. Using the Elastic Net estimator, we chose clusters of basis functions, and hence, rate constants of compartments. As further challenge, the estimator has to be restricted to positive regression parameters, which correspond to transfer rates of the compartments. The proposed estimation method is applied to an in-vivo data set

Spatially regularized estimation for the analysis of DCE-MRI data

Competing compartment models of different complexities have been used for the quantitative analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging data. We present a spatial Elastic Net approach that allows to estimate the number of compartments for each voxel such that the model complexity is not fixed a priori. A multi-compartment approach is considered, which is translated into a restricted least square model selection problem. This is done by using a set of basis functions for a given set of candidate rate constants. The form of the basis functions is derived from a kinetic model and thus describes the contribution of a specific compartment. Using a spatial Elastic Net estimator, we chose a sparse set of basis functions per voxel, and hence, rate constants of compartments. The spatial penalty takes into account the voxel structure of an image and performs better than a penalty treating voxels independently. The proposed estimation method is evaluated for simulated images and applied to an in-vivo data set

Supervised learning for analysing movement patterns in a virtual reality experiment

The projection into a virtual character and the concomitant illusionary body ownership can lead to transformations of one’s entity. Both during and after the exposure, behavioural and attitudinal changes may occur, depending on the characteristics or stereotypes associated with the embodied avatar. In the present study, we investigated the effects on physical activity when young students experience being old. After assignment (at random) to a young or an older avatar, the participants’ body movements were tracked while performing upper body exercises. We propose and discuss the use of supervised learning procedures to assign these movement patterns to the underlying avatar class in order to detect behavioural differences. This approach can be seen as an alternative to classical feature-wise testing. We found that the classification accuracy was remarkably good for support vector machines with linear kernel and deep learning by convolutional neural networks, when inserting time sub-sequences extracted at random and repeatedly from the original data. For hand movements, associated decision boundaries revealed a higher level of local, vertical positions for the young avatar group, indicating increased agility in their performances. This occurrence held for both guided movements as well as achievement-orientated exercises

Bacterial colonization within the first 6 weeks of life and pulmonary outcome in preterm infants <1000 g.

Bronchopulmonary dysplasia (BPD) is a multifactorial disease mainly provoked by pre- and postnatal infections, mechanical ventilation, and oxygen toxicity. In severely affected premature infants requiring mechanical ventilation, association of bacterial colonization of the lung and BPD was recently disclosed. To analyze the impact of bacterial colonization of the upper airway and gastrointestinal tract on moderate/severe BPD, we retrospectively analyzed nasopharyngeal and anal swabs taken weekly during the first 6 weeks of life at a single center inn= 102 preterm infants <1000 g. Colonization mostly occurred between weeks 2 and 6 and displayed a high diversity requiring categorization. Analyses of deviance considering all relevant confounders revealed statistical significance solely for upper airway colonization with bacteria with pathogenic potential and moderate/severe BPD (p= 0.0043) while no link could be established to the Gram response or the gastrointestinal tract. Our data highlight that specific colonization of the upper airway poses a risk to the immature lung. These data are not surprising taking into account the tremendous impact of microbial axes on health and disease across ages. We suggest that studies on upper airway colonization using predefined categories represent a feasible approach to investigate the impact on the pulmonary outcome in ventilated and non-ventilated preterm infants